Simplicity: The formula is straightforward and easy to understand. Sensitivity to Large Errors: The squaring of errors means that larger errors have a disproportionately large impact on the MSE, which is useful for identifying models that make significant mistakes. Comparative Tool: MSE allows for easy comparison between different models, helping researchers select the most accurate one.
